Different systems for analysis of vision components are known. Many of these systems, broadly categorized under machine vision, attempt to use the machine, usually a digital computer running dedicated software, to actually identify parts of the image.
However, vision algorithms frequently fail when confronted with real life images. These real life images may be of extremely high resolution, e.g., on the order of 6000 by 4000 pixels, and may be very cluttered with information that might not necessarily be relevant to the visual task at hand. For instance, many images may have partially occluding objects such as foliage, vehicles, people and so on.
It is believed that biological vision systems use a different approach. The mammalian visual system is believed to use a computational strategy of identifying interesting parts of the image without extensively analyzing the content of the image. The entire image may be analyzed in parallel for simple features. Portions of the image are then selected, based either on their behavioral relevance or based on local image cues. The local image cues may include brightness, motion, and/or color and others. The mammalian brain evolved in this manner to handle the enormous amount of information that is received from a scene. This information has been estimated as being on the order of up to 108 bits per second along the optic nerve, the axonal fibers that constitute the output of the retina. This may exceed what the brain is capable of fully processing and assimilating into its conscious experience.
Because of this processing strategy, only a small fraction of the information that is actually registered by the human visual system actually influences behavior. Different studies have demonstrated this in different ways. In some studies (“change blindness”) (Rensink, R. A., O'Regan, J. K., and Clark, J. J. “To see or not to see: The need for attention to perceive changes in scenes,” Psychological Sci. 8:368-373, 1997) significant image changes are not actually perceived under natural viewing conditions. However, once the attention of the person is directed to these changes, they can be easily perceived. This implies that even though a part of an image might be registered by the brain, the conscious mind might not be visually aware of that part or any other in the image.
Those parts of an image which elicit a strong, rapid and automatic response from viewers, independent of the task they are trying to solve, can be referred to as being “visually salient”. Two examples of such salient locations are a green object among red ones, or a vertical line among horizontal ones. The mind can direct its attention to other parts of the image, although that may require voluntary effort.